MODELING DOUBLE SCROLL TIME-SERIES

被引：3

作者：

DIMITRIADIS, A

FRASER, AM

机构：

[1] PORTLAND STATE UNIV,SYST SCI PROGRAM,PORTLAND,OR 97207

[2] PORTLAND STATE UNIV,DEPT ELECT ENGN,PORTLAND,OR 97207

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-ANALOG AND DIGITAL SIGNAL PROCESSING | 1993年 / 40卷 / 10期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1109/82.246171

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The ubiquity of strange attractors in nature suggests that nonlinear modeling techniques can improve performance in some signal processing applications. We introduce mixed state Markov models (MSMM's), a refinement of hidden filter HMM's, and apply both to a synthetic double scroll time series. Forecasts by HFHMM's diverge after a few steps. Using ad hoc procedures, forecasts by MSMM's, even models generated by crude methods without iterative optimization, can be made more stable.

引用

页码：683 / 687

页数：5

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